Curation of content generally refers to the process of collecting and maintaining long term repositories of assets for current and future reference by researchers, scientists, historians, scholars, and others. Curators of repositories of electronically stored assets face many challenges with respect to organizing and presenting electronically stored assets due not only to the immense size of some collections, but also the accelerating rate at which new assets are added and edited.
There are various systems and methods for acquiring, storing, and categorizing collections of electronically stored content. Some systems create and store metadata associated with the items in the collection that describe or relate to the content of the item. For example, some systems are specifically configured for electronically storing and organizing audiovisual data, such as videos, music, pictures, etc. Such audiovisual data, and other types of media data, can generically be referred to as content items. Content items can refer to any type of representation or expression of original, derived, and/or composite creation or collection of data and/or content. Content items can be stored in various electronic file formats in a variety of computer readable media.
Electronic media storage and retrieval systems often rely on the metadata associated with each content item for organization and search functions. The metadata for each content item usually includes a listing of keywords and descriptions about the actual contents of the content item. Such metadata can be created by the creator of the content item and/or added or edited by another system or user in various manual and automatic processes for describing the content of a content item. Conventional systems use integrated and external search engines to search and/or query the metadata associated with an electronically stored collection of content items to return one or more matches. Such systems may be helpful for smaller collections of content items, but can include various drawbacks for large collections of content items. For example, users are often presented with an overwhelming set of search results when only a few keywords are used in the search.
To address such issues, some conventional systems include the use of topical keyword lists and other structured knowledge data sources that can be topic oriented and help focus the scope of the returned content items. However, the results of a search or query issued to conventional content item repository that uses topical keyword lists and/or other structured knowledge data sources can still return an overwhelming number of content items. Accordingly, organizing and relating such large numbers of returned content items can be an arduous manual process.